diff options
Diffstat (limited to 'src/cpu/kernels/CpuWinogradConv2dKernel.cpp')
| -rw-r--r-- | src/cpu/kernels/CpuWinogradConv2dKernel.cpp | 106 |
1 files changed, 106 insertions, 0 deletions
diff --git a/src/cpu/kernels/CpuWinogradConv2dKernel.cpp b/src/cpu/kernels/CpuWinogradConv2dKernel.cpp new file mode 100644 index 0000000000..52e3f2549c --- /dev/null +++ b/src/cpu/kernels/CpuWinogradConv2dKernel.cpp @@ -0,0 +1,106 @@ +/* + * Copyright (c) 2017-2022 Arm Limited. + * + * SPDX-License-Identifier: MIT + * + * Permission is hereby granted, free of charge, to any person obtaining a copy + * of this software and associated documentation files (the "Software"), to + * deal in the Software without restriction, including without limitation the + * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or + * sell copies of the Software, and to permit persons to whom the Software is + * furnished to do so, subject to the following conditions: + * + * The above copyright notice and this permission notice shall be included in all + * copies or substantial portions of the Software. + * + * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR + * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, + * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE + * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER + * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, + * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE + * SOFTWARE. + */ + +#include "src/cpu/kernels/CpuWinogradConv2dKernel.h" + +namespace arm_compute +{ +namespace cpu +{ +CpuWinogradConv2dTransformInputKernel::CpuWinogradConv2dTransformInputKernel(arm_conv::winograd::WinogradImpl &w_impl, + arm_conv::ConvolutionArgs &_c_args, + uint32_t nthreads) + : _winograd_impl{w_impl}, _conv_args{_c_args}, _nthreads{nthreads} +{ +} + +void CpuWinogradConv2dTransformInputKernel::run_op(ITensorPack &tensors, const Window &window, const ThreadInfo &info) +{ + ARM_COMPUTE_UNUSED(window); + const ITensor *input_nhwc = tensors.get_const_tensor(TensorType::ACL_SRC); + const ITensor *winograd_input_transform = tensors.get_const_tensor(TensorType::ACL_DST); + const ITensor *workspace = tensors.get_const_tensor(TensorType::ACL_INT); + + const unsigned int width_idx = 1; + const unsigned int height_idx = 2; + const unsigned int batch_idx = 3; + int element_size_in_bytes = input_nhwc->info()->element_size(); + const auto src_strides = input_nhwc->info()->strides_in_bytes(); + + const size_t input_row_stride = src_strides[height_idx] / element_size_in_bytes; + const size_t input_col_stride = src_strides[width_idx] / element_size_in_bytes; + const size_t input_batch_stride = src_strides[batch_idx] / element_size_in_bytes; + const auto input_nhwc_ptr = + reinterpret_cast<const void *>(input_nhwc->buffer() + input_nhwc->info()->offset_first_element_in_bytes()); + auto win_transf_ptr = reinterpret_cast<void *>(winograd_input_transform->buffer() + + winograd_input_transform->info()->offset_first_element_in_bytes()); + + _winograd_impl.input_transform->execute(_conv_args, input_nhwc_ptr, input_batch_stride, input_row_stride, + input_col_stride, win_transf_ptr, _winograd_impl.winograd_spec, + workspace->buffer(), info.thread_id, _nthreads); +} + +CpuWinogradConv2dTransformOutputKernel::CpuWinogradConv2dTransformOutputKernel(arm_conv::winograd::WinogradImpl &w_impl, + arm_conv::ConvolutionArgs &_c_args, + uint32_t nthreads) + : _winograd_impl{w_impl}, _conv_args{_c_args}, _nthreads{nthreads} +{ +} + +// Inherited methods overridden: +void CpuWinogradConv2dTransformOutputKernel::run_op(ITensorPack &tensors, const Window &window, const ThreadInfo &info) +{ + ARM_COMPUTE_UNUSED(window); + const ITensor *dst_nhwc = tensors.get_const_tensor(TensorType::ACL_DST); + const ITensor *winograd_output_transform = tensors.get_const_tensor(TensorType::ACL_SRC_0); + const ITensor *biases = tensors.get_const_tensor(TensorType::ACL_SRC_1); + const ITensor *workspace = tensors.get_tensor(TensorType::ACL_INT); + + const unsigned int width_idx = 1; + const unsigned int height_idx = 2; + const unsigned int batch_idx = 3; + const int element_size_in_bytes = dst_nhwc->info()->element_size(); + const auto dst_strides = dst_nhwc->info()->strides_in_bytes(); + + const size_t out_row_stride = dst_strides[height_idx] / element_size_in_bytes; + const size_t out_col_stride = dst_strides[width_idx] / element_size_in_bytes; + const size_t out_batch_stride = dst_strides[batch_idx] / element_size_in_bytes; + const auto wout_transf_ptr = reinterpret_cast<const void *>( + winograd_output_transform->buffer() + winograd_output_transform->info()->offset_first_element_in_bytes()); + auto dst_nhwc_ptr = + reinterpret_cast<void *>(dst_nhwc->buffer() + dst_nhwc->info()->offset_first_element_in_bytes()); + void *biases_data_ptr = nullptr; + if (biases != nullptr) + { + biases_data_ptr = reinterpret_cast<void *>(biases->buffer() + biases->info()->offset_first_element_in_bytes()); + } + + // Output transform + _winograd_impl.output_transform->execute(_conv_args, wout_transf_ptr, _winograd_impl.winograd_spec, biases_data_ptr, + dst_nhwc_ptr, out_batch_stride, out_row_stride, out_col_stride, + workspace->buffer(), info.thread_id, _nthreads); +} + +} // namespace cpu +} // namespace arm_compute |